The present invention relates to image generation architectures, and more particularly, to an image generator architecture employing tri-level fixed interleave processing and distribution buses for use in image generation.
One problem relating to image generation is that visual systems substantially suffer in processing efficiency across all computational resources as a function of irregular and changing spatial distribution of the complexity of an image scene. Thus there is a need for an image generation architecture that maintains high processing efficiency that is independent of the spatial distribution of the image scene.
One primary architectural goal is to evenly distribute the computational load among processing resources. Pipeline approaches have been constrained to associate processing resources with display regions or channels. When image complexity becomes localized, some computational resources become overloaded while others are idle. Given the unpredictable nature of scene content in image generation, for example, scene complexity is frequently restricted to a localized viewport region or channel. Use of a pipeline architecture results in visual anomalies that are intrusive to training processes, for example.
A second problem relating to image generation is that visual systems cannot be configured to match specific polygon and pixel processing requirements for all applications. To solve this problem, the visual system should be reconfigurable through modularity, scalability, and real-time allocation of processing resources across channels. If a given application needs more polygon capacity, less pixel capacity, and more channel capacity than a nominal configuration, such needs should be achieved by independently adjusting the polygon, pixel, and video generation resources accordingly. With a fixed pipeline architecture in which the output of each stage feeds directly into the next, tuning the ratios among polygon, pixel, and display capacities is impossible.
Generating real-time images of a dynamic battlefield environment, for example, static allocation of processing resources on a per-channel basis yields overload on some channels while resources associated with other channels are underutilized. Traditionally, architectures have been designed so that computational resources are statically assigned to display channels. Such an approach works well for a three-channel configuration. Here, the polygon loading due to moving vehicles is uniform across the three channels, and each channel is at its maximum polygon capacity.
However, given the unpredictable motion of vehicles in a dynamic battlefield environment, such uniform loading of polygons among channels is unlikely. If the same scene is viewed from a different vantage point, all the polygons from the moving models are concentrated in the center channel.
A third problem relating to image generation is that visual systems cannot be configured to support a ratio of polygon performance relative to pixel performance of at least six polygons per thousand pixels. A review of the historical polygon and pixel performance requirements growth of a distributed interactive tactical team trainer manufactured by the assignee of the present invention, while the polygon and pixel performance requirements have grown, the ratio of polygon to pixel performance has remained within a narrow region of about 2 to 6 polygons per thousand pixels. Requirements for the next generation of distributed tactical team trainers have remained within these bounds.
Visual systems optimized for air vehicles have not been balanced for this required range of polygon to pixel performance ratio, typically providing a relatively large number of pixels compared to polygons. The ratios lie within a range of about 0.4 to 1.5 polygons per thousand pixels. This low ratio of polygons to pixels is correct for air vehicle simulators because three-dimensional complexity and depth complexity are very low when the real-world is simulated for higher altitudes.
Because an image generator's architecture determine the optimal operating range of polygons to pixels, for a machine to be optimized for a wide range of image generation applications, it must be designed to achieve this from the start. In addition, such a system should be modular and scalable to allow each image generator to be configured for precise polygon and pixel loading requirements of the trainer coupled to it.
Therefore, it is an objective of the present invention to provide for an image generator architecture for use in image generation systems such as training simulators, and the like, that overcomes the above-mentioned problems.